[{"data":1,"prerenderedAt":792},["ShallowReactive",2],{"/en-us/blog/the-consul-outage-that-never-happened":3,"navigation-en-us":35,"banner-en-us":435,"footer-en-us":445,"blog-post-authors-en-us-Devin Sylva":687,"blog-related-posts-en-us-the-consul-outage-that-never-happened":701,"assessment-promotions-en-us":743,"next-steps-en-us":782},{"id":4,"title":5,"authorSlugs":6,"body":8,"categorySlug":9,"config":10,"content":14,"description":8,"extension":24,"isFeatured":12,"meta":25,"navigation":26,"path":27,"publishedDate":20,"seo":28,"stem":32,"tagSlugs":33,"__hash__":34},"blogPosts/en-us/blog/the-consul-outage-that-never-happened.yml","The Consul Outage That Never Happened",[7],"devin-sylva",null,"engineering",{"slug":11,"featured":12,"template":13},"the-consul-outage-that-never-happened",false,"BlogPost",{"title":15,"description":16,"authors":17,"heroImage":19,"date":20,"body":21,"category":9,"tags":22},"The Consul outage that never happened","Sometimes a good plan is the best tool for the job.",[18],"Devin Sylva","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749679092/Blog/Hero%20Images/consul-outage-image.jpg","2019-11-08","When things go wrong on a large website, it can be fun to read the dramatic stories of high pressure incidents where nothing goes as planned. It makes for good reading. Every once in a while though, we get a success story. Every once in a while, things go exactly as planned.\n\n[GitLab.com](http://GitLab.com) is a large, high availability instance of GitLab. It is maintained by the [Infrastructure group](/company/team/?department=infrastructure-department), which currently consists of 20 to 24 engineers (depending on how you count), four managers, and a director, distributed all around the world. Distributed, in this case, does not mean across a few different offices. There are three or four major cities which have more than one engineer but with the exception of coworking days nobody is working from the same building.\n\nIn order to handle the load generated by about four million users working on around 12 million projects, GitLab.com breaks out the individual components of the GitLab product and currently spreads them out over 271 production servers.\n\nThe site is slowly migrating to using Hashicorp's [Consul](https://www.consul.io) for service location. Consul can be thought of like DNS, in that it associates a well-known name with the actual physical location of that service. It also provides other useful functions such as storing dynamic configuration for services, as well as locking for clusters. All of the Consul client and server components talk to each other over encrypted connections. These connections require a certificate at each end to validate the identity of the client and server and to provide the encryption key. The main component of GitLab.com which currently relies on this service is the database and its high availability system [Patroni](https://patroni.readthedocs.io/en/latest/). Like any website that provides functionality and not just information, the database is the central service that everything else depends on. Without the database, the website, API, CI pipelines, and git services will all deny requests and return errors.\n\n## Troubleshooting\n\nThe [issue](https://gitlab.com/gitlab-com/gl-infra/production/issues/1037) came to our attention when a database engineer noticed that one of our database servers in the staging environment could not reconnect to the staging Consul server after the database node was restarted.\n\nIt turns out that the TLS certificate was expired. This is normally a simple fix. Someone would go to the Certificate Authority (CA) and request a renewal – or if that fails, generate a new certificate to be signed by the same CA. That certificate would replace the expired copy and the service would be restarted. All of the connections should reestablish using the new certificate and just like with any other rolling configuration change, it should be transparent to all users.\n\nAfter looking everywhere, and asking everyone on the team, we got the definitive answer that the CA key we created a year ago for this self-signed certificate had been lost.\n\nThese test certificates were generated for the original proof-of-concept installation for this service and were never intended to be transitioned into production. However, since everything was working perfectly, the expired test certificate had not been calling attention to itself. A few things should have been done, including: Rebuilding the service with production in mind; conducting a production readiness review; and monitoring. But a year ago, our production team was in a very different place. We were small with just four engineers, and three new team members: A manager, director, and engineer, all of whom were still onboarding. We were less focused on the gaps that led to this oversight a year ago and more focused on fixing the urgent problem today.\n\n### Validating the problem\n\nFirst, we needed to validate the problem using the information we'd gathered. Since we couldn't update the existing certificates, we turned validation off on the client that couldn't connect. Turning validation off didn't change anything since the encrypted connections validate both the cluster side and client side. Next, we changed the setting on one server node in the cluster and so the restarted client could then connect to the server node. The problem now was that the server could no longer connect to any other cluster node and could not rejoin the cluster. The server we changed was not validating connections, meaning it was ignoring the expired certificate of its peers in the cluster but the peers were not returning the favor. They were shunning it, putting the whole cluster in a degraded state.\n\nWe realized that no matter what we did, some servers and some clients would not be able to connect to each other until after the change had been made everywhere and after every service was restarted. Unfortunately, we were talking about 255 of our 271 servers. Our tool set is designed for gradual rollouts, not simultaneous actions.\n\nWe were unsure why the site was even still online because if the clients and services could not connect it was unclear why anything was still working. We ran a small test, confirming the site was only working because the connections were already established when the certificates expired. Any interruption of these long-running connections would cause them to revalidate the new connections, resulting in them rejecting all new connections across the fleet.\n\n> Effectively, we were in the middle of an outage that had already started, but hadn't yet gotten to the point of taking down the site.\n\n### Testing in staging\n\nWe declared an incident and began testing every angle we could think of in the staging environment, including:\n\n* Reloading the configuration of the running service, which worked fine and did not drop connections, but the [certificate settings](https://github.com/hashicorp/consul/pull/4204) are [not included in the reloadable settings](https://www.consul.io/docs/agent/options.html#reloadable-configuration) for our version of Consul.\n* Simultaneous restarts of various services, which worked, but our tools wouldn't allow us to do that with ALL of the nodes at once.\n\nEverything we tried indicated that we had to break those existing connections in order to activate any change, and that we could only avoid downtime if that happened on **ALL nodes at precisely the same time**.\n\nEvery problem uncovered other problems and as we were troubleshooting one of our production Consul servers became unresponsive, disconnected all SSH sessions, and would not allow anyone to reconnect. The server did not log any errors. It was still sending monitoring data and was still participating in the Consul cluster. If we restarted the server, then it would not have been able to reconnect to its peers and we would have an even number of nodes. Not having quorum in the cluster would have been dangerous when we went to restart all of the nodes, so we left it in that state for the moment.\n\n## Planning\n\nOnce the troubleshooting was finished [it was time to start planning](https://gitlab.com/gitlab-com/gl-infra/production/issues/1042).\n\nThere were a few ways to solve the problem. We could:\n\n* Replace the CA and the certificates with new self-signed ones.\n* Change the CA setting to point to the system store, allowing us to use certificates signed by our standard certificate provider and then replace the certificates.\n* Disable the validation of the dates so that the expired certificate would not cause connections to fail.\n\nAll of these options would incur the same risks and involve the same risky restart of all services at once.\n\nWe picked the last option. Our reasoning was that disabling the validation would eliminate the immediate risk and give us time to slowly roll out a properly robust solution in the near future, without having to worry about disrupting the whole system. It was also the [smallest and most incremental change](https://handbook.gitlab.com/handbook/values/#iteration).\n\n### Working asynchronously to tackle the problem\n\nWhile there was some time pressure due to the [risk of network connections being interrupted](https://gitlab.com/gitlab-com/gl-infra/production/issues/1037#note_201745119), we had to consider the reality of working across timezones as we planned our solution.\n\n> We decided not to hand it off to the European shift, who were coming online soon. Being a [globally distributed](https://handbook.gitlab.com/handbook/company/culture/all-remote/) team, we had already handed things off from the end of the day in Mongolia, through Eastern and Western Europe and across the Americas, and were approaching the end of the day in Hawaii and New Zealand.\n\nAustralia still had a few more hours and Mongolia had started the day again, but the folks who had been troubleshooting it throughout the day had a pretty good handle on what needed to happen and what could go wrong. It made sense for them to be the ones to do the work. We decided to make a \"Break Glass\" plan instead. This was a merge request with all of the changes and information necessary for the European shift to get us back into a good state in case a full outage happened before anyone who had been working on it woke up. Everyone slept better knowing that we had a plan that would work even if it could not be executed without causing down time. If we were already experiencing down time, there would be no problem.\n\n### Designing our approach\n\nIn the morning (HST) everything was how we left it so we started planning how to change the settings and restart all of the services without downtime. Our normal management tools were out because of the time it takes to roll out changes. Even sequential tools such as `knife ssh`, `mussh`, or `ansible` wouldn't work because the change had to be **precisely simultaneous**. Someone joked about setting it up in `cron` which led us to the standard linux `at` command (a relative of the more widely used `batch`). `cron` would require cleanup afterward but an `at` command can be pushed out ahead of time with a sequential tool and will run a command at a precise time on all machines. Back in the days of hands-on, bare metal system administration, it was a useful trick for running one-time maintenance in the middle of the night or making it look like you were working when you weren't. Now `at` has become more obscure with the trend toward managing fleets of servers rather than big monolithic central machines. We chose to run the command `sudo systemctl restart consul.service`. We tested this in staging to verify that our Ubuntu distribution made environment variables like `$PATH` available, and that `sudo` did not ask for a password. On some distributions (older CentOS especially) this is not always the case.\n\nWith those successful tests, we still needed to change the config files. Luckily, there is nothing that prevents changing these ahead of time since the changes aren't picked up until the service restarts. We didn't want to do this step at the same time as the service restart so we could validate the changes and keep the `at` command as small as possible. We decided not to use Chef to push out the change because we needed complete and immediate transparency. Any nodes that did not get the change would fail after the restart. `mussh` was the tool that offered the most control and visibility while still being able to change all hosts with one command.\n\nWe also had to disable the Chef client so that it didn't overwrite the changes between when they were written and when the service restarted.\n\nBefore running anything we also needed to address the one Consul server that we couldn't access. It likely just needed to be rebooted and would come up and be unable to reconnect to the cluster. The best option was to do this manually just before starting the rest of the procedure.\n\nOnce we had mapped out the plan we practiced it in the disaster recovery environment. We used the disaster recovery environment instead of the staging environment because all of the nodes in the staging environment had already been restarted, so there were no long-running connections to test. Making the disaster recovery environment was the next best option. It did not go perfectly since the database in this environment was already in an unhealthy state but it gave us valuable information to adjust the plan.\n\n## Pre-execution\n\n### A moment of panic\n\nIt was almost time to fix the inaccessible Consul node. The team connected in to one of the other nodes to monitor and watch logs. Suddenly, the second node started disconnecting people. It was behaving exactly like the inaccessible node had the previous day. 😱 Suspiciously, it didn't disconnect everyone. Those who were still logged in noticed that `sshguard` was blocking access to some of the bastion servers that all of our ssh traffic flows through when accessing the internal nodes: [Infrastructure#7484](https://gitlab.com/gitlab-com/gl-infra/infrastructure/issues/7484). We have three bastion servers, and two were blocked because so many of us connected so many sessions so quickly. Disabling `sshguard` allowed everyone back in and that information was the hint we needed to manually find the one bastion which hadn't yet been blocked. It got us back into the original problem server. Disabling `sshguard` there left us with a fully functional node and with the ability to accept the `at` command to restart the Consul service at exactly the same time as the others.\n\nWe verified that we had an accurate and instantaneous way to monitor the state of the services. Watching the output of the `consul operator raft list-peers` command every second gave us view that looked like this:\n\n```text\nNode                Address          State     Voter  RaftProtocol\nconsul-01-inf-gprd  10.218.1.4:8300  follower  true   3\nconsul-03-inf-gprd  10.218.1.2:8300  leader    true   3\nconsul-05-inf-gprd  10.218.1.6:8300  follower  true   3\nconsul-04-inf-gprd  10.218.1.5:8300  follower  true   3\nconsul-02-inf-gprd  10.218.1.3:8300  follower  true   3\n```\n\n### More nodes, more problems\n\nEven the most thorough plans always miss something. At this point we realized that one of the three `pgbouncer` nodes which direct traffic to the correct database instance was not showing as healthy in the load balancer. One is normally in this state as a warm spare, but one of the side effects of disconnecting the `pgbouncer` nodes from Consul is that they would all fail their load balancer health checks. If all health checks are failing, GCP load balancers send requests to ALL nodes as a safety feature. This would lead to too many connections to our database servers, causing unintended consequences. We worked around this by removing the unhealthy node from the load balancer pool for the remainder of this activity.\n\n* We checked that the lag on the database replicas was zero, and that they weren't trying to replicate any large and time-consuming transactions.\n* We generated a text list of all of the nodes that run the Consul client or server.\n* We verified the time zone (UTC) and time synchronization on all of those servers to ensure that when the `at` command executed the restart, an unsynchronized clock wouldn't cause unintended behavior.\n* We also verified the `at` scheduler was running on all of those nodes, and that `sudo` would not ask for a password.\n* We verified the script that would edit the config files, and tested it against the staging environment.\n* We also made sure `sshguard` was disabled and wasn't going to lock out the scripted process for behaving like a scripted process.\n\nThis might seem like a lot of steps but without any of these prerequisites the whole process would fail. Once all of that was done, everything was ready to go.\n\n## Execution\n\nIn the end, we scheduled a maintenance window and distilled all of the research and troubleshooting down to the [steps in this issue](https://gitlab.com/gitlab-com/gl-infra/production/issues/1042).\n\nEverything was staged and it was time to make the changes. This course of action included four key steps. First, we paused the Patroni database high availability subsystem. Pausing would freeze database failover and keep the high availability configuration static until we were done. It would have been bad if we had a database failure during this time so minimizing the amount of time in this state was important.\n\nNext, we ran a script on every machine that stopped the Chef client service and then changed the verify lines in the config files from true to false. It wouldn't help to have Chef trying to reconfigure anything as we made changes. We did this using `mussh` in batches of 20 servers at a time. Any more in parallel and our SSH agent and Yubikeys may not have been able to keep up. We were not expecting change in the state of anything from this step. The config files on disk should have the new values but the running services wouldn't change, and more importantly, no TCP connections would disconnect. That was what we got so it was time for some verification.\n\nOur third step was to check all of the servers and a random sampling of client nodes to make sure config files had been modified appropriately. It was also a good time to double-check that the Chef client was disabled. This check turned out to be a good thing to do, because there were a few nodes that still had the Chef client active. It turned out that those nodes were in the middle of a run when we disabled the service, and it reenabled the service for us when the run completed. Chef can be _so_ helpful. We disabled it manually on the few machines that were affected. This delayed our maintenance window by a few minutes, so we were very glad we didn't schedule the `at` commands first.\n\nFinally, we needed to remove the inactive `pgbouncer` node from the load balancer, so when the load balancer went into its safety mode, it would only send traffic to the two that were in a known state. You might think that removing it from the load balancer would be enough, but since it also participates in a cluster via Consul the whole service needed to be shut down along with the health check, which the load balancer uses to determine whether to send it traffic. We made a note of the full command line from the process table, shut it down, and removed it from the pool.\n\n### The anxiety builds\n\nNow was the moment of truth. It was 02:10 UTC. We pushed the following command to every server (20 at a time, using `mussh`): `echo 'sudo systemctl restart consul.service' | at 02:20` – it took about four minutes to complete. Then we waited. We monitored the Consul servers by running `watch -n 1 consul operator raft list-peers` on each of them in a separate terminal. We bit our nails. We watched the dashboards for signs of db connection errors from the frontend nodes. We all held our breath, and watched the database for signs of distress. Six minutes is a long time to think: \"It's 4am in Europe, so they won't notice\" and \"It's dinner time on the US west coast, maybe they won't notice\". Trust me, six minutes is a _really_ long time: \"Sorry APAC users for your day, which we are about to ruin by missing something\".\n\nWe counted down the last few seconds and watched. In the first second, the Consul servers all shut down, severing the connections that were keeping everything working. All 255 of the clients restarted at the same time. In the next second, we watched the servers return `Unexpected response code: 500`, which means \"connection refused\" in this case. The third second... still returning \"panic now\" or maybe it was \"connection refused\"... The fourth second all nodes returned `no leader found`, which meant that the connection was not being refused but the cluster was not healthy. The fifth second, no change. I'm thinking, just breathe, they were probably all discovering each other. In the sixth second, still no change: Maybe they're electing a leader? Second seven was the appropriate time for worry and panic. Then, the eighth second brought good news `node 04 is the leader`. All other nodes healthy and communicating properly. In the ninth second, we let out a collective (and globally distributed) exhale.\n\n### A quick assessment\n\nNow it was time to check what damage that painfully long eight seconds had done. We went through our checklist:\n\n* The database was still processing requests, no change.\n* The web and API nodes hadn't thrown any errors. They must have restarted fast enough that the cached database addresses were still being used.\n* The most important metric – the graph of 500 errors seen by customers: There was no change.\n\nWe expected to see a small spike in errors, or at least some identifiable change, but there was nothing but the noise floor. This was excellent news! 🎉\n\nThen we checked whether the database was communicating with the Consul servers. It was not. Everyone quickly turned their attention to the backend database servers. If they had been running normally and the high availability tool hadn't been paused, an unplanned failover would be the minimum outage we could have hoped for. It's likely that they would have gotten into a very bad state. We started to troubleshoot why it wasn't communicating with the Consul server, but about one minute into the change, the connection came up and everything synced. Apparently it just needed a little more time than the others. We verified everything, and when everyone was satisfied we turned the high availability back on.\n\n## Cleanup\n\nNow that everything in the critical path was working as expected, we released the tension from our shoulders. We re-enabled Chef and merged the MR pinning the Chef recipes to the newer version, and the MR's CI job pushed the newer version to our Chef server. After picking a few low-impact servers, we manually kicked off Chef runs after checking the `md5sum` of the Consul client config files. After Chef finished, there was no change to the file, and the Chef client service was running normally again. We followed the same process on the Consul servers with the same result, and manually implemented it on the database servers, just for good measure. Once those all looked good, we used `mussh` to kick off a Chef run on all of the servers using the same technique we used to turn them off.\n\nNow all that was left was to straighten everything out with `pgbouncer` and the database load balancer and then we could fully relax. Looking at the heath checks, we noticed that the two previously healthy nodes were not returning healthy. The health checks are used to tell the load balancer which `pgbouncer` nodes have a Consul lock and therefore which nodes to send the traffic. A little digging showed that after retrying to connect to the Consul service a few times, they gave up. This was not ideal, so we [opened an Infrastructure issue](https://gitlab.com/gitlab-com/gl-infra/infrastructure/issues/7612) to fix it later and restarted the health checks manually. Everything showed normal so we added the inactive node back to the load balancer. The inactive node's health check told the load balancer not to select it, and since the load balancer was no longer in failsafe mode (due to the other node's health checks succeeding) the load balancer refrained from sending it traffic.\n\n## Conclusion\n\nSimultaneously restarting all of the Consul components with the new configuration put everything back into its original state, other than the validation setting which we set to false, and the TCP sessions which we restarted. After this change, the Consul clients will still be using TLS encryption but will ignore the fact that our cert is now expired. This is still not an ideal state but it gives us time to get there in a thoughtful way rather than as a rushed workaround.\n\nEvery once in a while we get into a situation that all of the fancy management tools just can't fix. There is no run book for situations such as the one we encountered. The question we were asked most frequently once people got up to speed was: \"Isn't there some instructional walkthrough published somewhere for this type of thing?\". For replacing a certificate from the same authority, yes definitely. For replacing a certificate on machines that can have downtime, there are plenty. But for keeping traffic flowing when hundreds of nodes need to change a setting and reconnect within a few seconds of each other... that's just not something that comes up very often. Even if someone wrote up the procedure it wouldn't work in our environment with all of the peripheral moving parts that required our attention.\n\nIn these types of situations there is no shortcut around thinking things through methodically. In this case, there were no tools or technologies that could solve the problem. Even in this new world of infrastructure as code, site reliability engineering, and cloud automation, there is still room for old fashioned system administrator tricks. There is just no substitute for understanding how everything works. We can try to abstract it away to make our day-to-day responsibilities easier, but when it comes down to it there will always be times when the best tool for the job is a solid plan.\n\nCover image by [Thomas Jensen](https://unsplash.com/@thomasjsn?utm_source=unsplash&utm_medium=referral&utm_content=creditCopyText) on 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IIT Bombay students are coding the future with GitLab","At GitLab, we often talk about how software accelerates innovation. But sometimes, you have to step away from the Zoom calls and stand in a crowded university hall to remember why we do this.",[707],"Nick Veenhof","https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099013/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2814%29_6VTUA8mUhOZNDaRVNPeKwl_1750099012960.png","2026-01-08",[257,609,711],"open source","The GitLab team recently had the privilege of judging the **iHack Hackathon** at **IIT Bombay's E-Summit**. The energy was electric, the coffee was flowing, and the talent was undeniable. But what struck us most wasn't just the code — it was the sheer determination of students to solve real-world problems, often overcoming significant logistical and financial hurdles to simply be in the room.\n\n\nThrough our [GitLab for Education program](https://about.gitlab.com/solutions/education/), we aim to empower the next generation of developers with tools and opportunity. Here is a look at what the students built, and how they used GitLab to bridge the gap between idea and reality.\n\n## The challenge: Build faster, build securely\n\nThe premise for the GitLab track of the hackathon was simple: Don't just show us a product; show us how you built it. We wanted to see how students utilized GitLab's platform — from Issue Boards to CI/CD pipelines — to accelerate the development lifecycle.\n\nThe results were inspiring.\n\n## The winners\n\n### 1st place: Team Decode — Democratizing Scientific Research\n\n**Project:** FIRE (Fast Integrated Research Environment)\n\nTeam Decode took home the top prize with a solution that warms a developer's heart: a local-first, blazing-fast data processing tool built with [Rust](https://about.gitlab.com/blog/secure-rust-development-with-gitlab/) and Tauri. They identified a massive pain point for data science students: existing tools are fragmented, slow, and expensive.\n\nTheir solution, FIRE, allows researchers to visualize complex formats (like NetCDF) instantly. What impressed the judges most was their \"hacker\" ethos. They didn't just build a tool; they built it to be open and accessible.\n\n**How they used GitLab:** Since the team lived far apart, asynchronous communication was key. They utilized **GitLab Issue Boards** and **Milestones** to track progress and integrated their repo with Telegram to get real-time push notifications. As one team member noted, \"Coordinating all these technologies was really difficult, and what helped us was GitLab... the Issue Board really helped us track who was doing what.\"\n\n![Team Decode](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/epqazj1jc5c7zkgqun9h.jpg)\n\n### 2nd place: Team BichdeHueDost — Reuniting to Solve Payments\n\n**Project:** SemiPay (RFID Cashless Payment for Schools)\n\nThe team name, BichdeHueDost, translates to \"Friends who have been set apart.\" It's a fitting name for a group of friends who went to different colleges but reunited to build this project. They tackled a unique problem: handling cash in schools for young children. Their solution used RFID cards backed by a blockchain ledger to ensure secure, cashless transactions for students.\n\n**How they used GitLab:** They utilized [GitLab CI/CD](https://about.gitlab.com/topics/ci-cd/) to automate the build process for their Flutter application (APK), ensuring that every commit resulted in a testable artifact. This allowed them to iterate quickly despite the \"flaky\" nature of cross-platform mobile development.\n\n![Team BichdeHueDost](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/pkukrjgx2miukb6nrj5g.jpg)\n\n### 3rd place: Team ZenYukti — Agentic Repository Intelligence\n\n**Project:** RepoInsight AI (AI-powered, GitLab-native intelligence platform)\n\nTeam ZenYukti impressed us with a solution that tackles a universal developer pain point: understanding unfamiliar codebases. What stood out to the judges was the tool's practical approach to onboarding and code comprehension: RepoInsight-AI automatically generates documentation, visualizes repository structure, and even helps identify bugs, all while maintaining context about the entire codebase.\n\n**How they used GitLab:** The team built a comprehensive CI/CD pipeline that showcased GitLab's security and DevOps capabilities. They integrated [GitLab's Security Templates](https://gitlab.com/gitlab-org/gitlab/-/tree/master/lib/gitlab/ci/templates/Security) (SAST, Dependency Scanning, and Secret Detection), and utilized [GitLab Container Registry](https://docs.gitlab.com/user/packages/container_registry/) to manage their Docker images for backend and frontend components. They created an AI auto-review bot that runs on merge requests, demonstrating an \"agentic workflow\" where AI assists in the development process itself.\n\n![Team ZenYukti](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380253/ymlzqoruv5al1secatba.jpg)\n\n## Beyond the code: A lesson in inclusion\n\nWhile the code was impressive, the most powerful moment of the event happened away from the keyboard.\n\nDuring the feedback session, we learned about the journey Team ZenYukti took to get to Mumbai. They traveled over 24 hours, covering nearly 1,800 kilometers. Because flights were too expensive and trains were booked, they traveled in the \"General Coach,\" a non-reserved, severely overcrowded carriage.\n\nAs one student described it:\n\n*\"You cannot even imagine something like this... there are no seats... people sit on the top of the train. This is what we have endured.\"*\n\nThis hit home. [Diversity, Inclusion, and Belonging](https://handbook.gitlab.com/handbook/company/culture/inclusion/) are core values at GitLab. We realized that for these students, the barrier to entry wasn't intellect or skill, it was access.\n\nIn that moment, we decided to break that barrier. We committed to reimbursing the travel expenses for the participants who struggled to get there. It's a small step, but it underlines a massive truth: **talent is distributed equally, but opportunity is not.**\n\n![hackathon class together](https://res.cloudinary.com/about-gitlab-com/image/upload/v1767380252/o5aqmboquz8ehusxvgom.jpg)\n\n### The future is bright (and automated)\n\nWe also saw incredible potential in teams like Prometheus, who attempted to build an autonomous patch remediation tool (DevGuardian), and Team Arrakis, who built a voice-first job portal for blue-collar workers using [GitLab Duo](https://about.gitlab.com/gitlab-duo/) to troubleshoot their pipelines.\n\nTo all the students who participated: You are the future. Through [GitLab for Education](https://about.gitlab.com/solutions/education/), we are committed to providing you with the top-tier tools (like GitLab Ultimate) you need to learn, collaborate, and change the world — whether you are coding from a dorm room, a lab, or a train carriage. **Keep shipping.**\n\n> :bulb: Learn more about the [GitLab for Education program](https://about.gitlab.com/solutions/education/).\n",{"slug":714,"featured":12,"template":13},"how-iit-bombay-students-code-future-with-gitlab",{"content":716,"config":725},{"title":717,"description":718,"authors":719,"heroImage":720,"date":721,"category":9,"tags":722,"body":724},"Artois University elevates research and curriculum with GitLab Ultimate for Education","Artois University's CRIL leveraged the GitLab for Education program to gain free access to Ultimate, transforming advanced research and computer science curricula.",[707],"https://res.cloudinary.com/about-gitlab-com/image/upload/v1750099203/Blog/Hero%20Images/Blog/Hero%20Images/blog-image-template-1800x945%20%2820%29_2bJGC5ZP3WheoqzlLT05C5_1750099203484.png","2025-12-10",[609,257,723],"product","Leading academic institutions face a critical challenge: how to provide thousands of students and researchers with industry-standard, **full-featured DevSecOps tools** without compromising institutional control. Many start with basic version control, but the modern curriculum demands integrated capabilities for planning, security, and advanced CI/CD.\n\nThe **GitLab for Education program** is designed to solve this by providing access to **GitLab Ultimate** for qualifying institutions, allowing them to scale their operations and elevate their academic offerings. \n\nThis article showcases a powerful success story from the **Centre de Recherche en Informatique de Lens (CRIL)**, a joint laboratory of **Artois University** and CNRS in France. After years of relying solely on GitLab Community Edition (CE), the university's move to GitLab Ultimate through the GitLab for Education program immediately unlocked advanced capabilities, transforming their teaching, research, and contribution workflows virtually overnight. This story demonstrates why GitLab Ultimate is essential for institutions seeking to deliver advanced computer science and research curricula.\n\n## GitLab Ultimate unlocked: Managing scale and driving academic value\n\n**Artois University's** self-managed GitLab instance is a large-scale operation, supporting nearly **3,000 users** across approximately **19,000 projects**, primarily serving computer science students and researchers. While GitLab Community Edition was robust, the upgrade to GitLab Ultimate provided the sophisticated tooling necessary for managing this scale and facilitating advanced university-level work.\n\n***\"We can see the difference,\" says Daniel Le Berre, head of research at CRIL and the instance maintainer. \"It's a completely different product. Each week reveals new features that directly enhance our productivity and teaching.\"***\n\nThe institution joined the GitLab for Education program specifically because it covers both **instructional and non-commercial research use cases** and offers full access to Ultimate's features, removing significant cost barriers.\n\n### Key GitLab Ultimate benefits for students and researchers\n\n* **Advanced project management at scale:** Master's students now benefit from **GitLab Ultimate's project planning features**. This enables them to structure, track, and manage complex, long-term research projects using professional methodologies like portfolio management and advanced issue tracking that seamlessly roll up across their thousands of projects.\n\n* **Enhanced visibility:** Features like improved dashboards and code previews directly in Markdown files dramatically streamline tracking and documentation review, reducing administrative friction for both instructors and students managing large project loads.\n\n## Comprehensive curriculum: From concepts to continuous delivery\n\nGitLab Ultimate is deeply integrated into the computer science curriculum, moving students beyond simple `git` commands to practical **DevSecOps implementation**.\n\n* **Git fundamentals:** Students begin by visualizing concepts using open-source tools to master Git concepts.\n\n* **Full CI/CD implementation:** Students use GitLab CI for rigorous **Test-Driven Development (TDD)** in their software projects. They learn to build, test, and perform quality assurance using unit and integration testing pipelines—core competency made seamless by the integrated platform.\n\n* **DevSecOps for research and documentation:** The university teaches students that DevSecOps principles are vital for all collaborative work. Inspired by earlier work in Delft, students manage and produce critical research documentation (PDFs from Markdown files) using GitLab, incorporating quality checks like linters and spell checks directly in the CI pipeline. This ensures high-quality, reproducible research output.\n\n* **Future-proofing security skills:** The GitLab Ultimate platform immediately positions the institution to incorporate advanced DevSecOps features like SAST and DAST scanning as their research and development code projects grow, ensuring students are prepared for industry security standards.\n\n## Accelerating open source contributions with GitLab Duo\n\nAccess to the full GitLab platform, including our AI capabilities, has empowered students to make impactful contributions to the wider open source community faster than ever before.\n\nTwo Master's students recently completed direct contributions to the GitLab product, adding the **ORCID identifier** into user profiles. Working on GitLab.com, they leveraged **GitLab Duo's AI chat and code suggestions** to navigate the codebase efficiently.\n\n***\"This would not have been possible without GitLab Duo,\" Daniel Le Berre notes. \"The AI features helped students, who might have lacked deep codebase knowledge, deliver meaningful contributions in just two weeks.\"***\n\nThis demonstrates how providing students with cutting-edge tools **accelerates their learning and impact**, allowing them to translate classroom knowledge into real-world contributions immediately.\n\n## Empowering open research and institutional control\n\nThe stability of the self-managed instance at Artois University is key to its success. This model guarantees **institutional control and stability** — a critical factor for long-term research preservation.\n\nThe institution's expertise in this area was recently highlighted in a major 2024 study led by CRIL, titled: \"[Higher Education and Research Forges in France - Definition, uses, limitations encountered and needs analysis](https://hal.science/hal-04208924v4)\" ([Project on GitLab](https://gitlab.in2p3.fr/coso-college-codes-sources-et-logiciels/forges-esr-en)). The research found that the vast majority of public forges in French Higher Education and Research relied on **GitLab**. This finding underscores the consensus among academic leaders that self-hosted solutions are essential for **data control and longevity**, especially when compared to relying on external, commercial forges.\n\n## Unlock GitLab Ultimate for your institution today\n\nThe success story of **Artois University's CRIL** proves the transformative power of the GitLab for Education program. By providing **free access to GitLab Ultimate**, we enable large-scale institutions to:\n\n1.  **Deliver a modern, integrated DevSecOps curriculum.**\n\n2.  **Support advanced, collaborative research projects with Ultimate planning features.**\n\n3.  **Empower students to make AI-assisted open source contributions.**\n\n4.  **Maintain institutional control and data longevity.**\n\nIf your academic institution is ready to equip its students and researchers with the complete DevSecOps platform and its most advanced features, we invite you to join the program.\n\nThe program provides **free access to GitLab Ultimate** for qualifying instructional and non-commercial research use cases.\n\n**Apply now [online](https://about.gitlab.com/solutions/education/join/).**\n",{"slug":726,"featured":26,"template":13},"artois-university-elevates-curriculum-with-gitlab-ultimate-for-education",{"content":728,"config":741},{"category":9,"tags":729,"body":732,"date":733,"updatedDate":734,"heroImage":735,"authors":736,"title":739,"description":740},[730,731,104],"tutorial","git","\nEnterprise teams are increasingly migrating from Azure DevOps to GitLab to gain strategic advantages and accelerate secure software delivery. \n\n\n- GitLab comes with integrated controls, policies, and [compliance frameworks](https://docs.gitlab.com/user/compliance/compliance_frameworks/) that allow organizations to implement software delivery standards at scale. This is especially important for regulated industries.\n\n- [Security testing](https://docs.gitlab.com/user/application_security/) is embedded in the pipeline and results show in the developer workflow, including static application security testing (SAST), source code analysis (SCA), dynamic application security testing (DAST), infrastructure-as-code scanning (IaC), container scanning, and API scanning.\n\n- [AI capabilities](https://about.gitlab.com/gitlab-duo-agent-platform/) across the full software delivery lifecycle include advanced agent orchestration and customizable flows to support how your organizational teams work.\n\n\nGitLab's open-source, open-core approach, flexible deployment options such as single-tenant dedicated and self-managed, and truly unified platform eliminate integration complexity and security gaps. \n\n\nFor teams facing mounting pressure to accelerate delivery while strengthening security posture and maintaining regulatory compliance, GitLab represents not just a migration but a platform evolution.\n\n\nMigrating from Azure DevOps to GitLab can seem like a daunting task, but with the right approach and tools, it can be a smooth and efficient process. This guide will walk you through the steps needed to successfully migrate your projects, repositories, and pipelines from Azure DevOps to GitLab.\n\n\n## Overview\n\nGitLab provides both [Congregate](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/) (maintained by [GitLab Professional Services](https://about.gitlab.com/professional-services/) organization) and [a built-in Git repository import](https://docs.gitlab.com/user/project/import/repo_by_url/) for migrating projects from Azure DevOps (ADO). These options support repository-by-repository or bulk migration and preserve git commit history, branches, and tags. With Congregate and professional services tools, we support additional assets such as wikis, work items, CI/CD variables, container images, packages, pipelines, and more (see this [feature matrix](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/blob/master/customer/ado-migration-features-matrix.md)). Use this guide to plan and execute your migration and complete post-migration follow-up tasks.\n\n\nEnterprises migrating from ADO to GitLab commonly follow a multi-phase approach:\n\n\n- Migrate repositories from ADO to GitLab using Congregate or GitLab's built-in repository migration.\n\n- Migrate pipelines from Azure Pipelines to GitLab CI/CD.\n\n- Migrate remaining assets such as boards, work items, and artifacts to GitLab Issues, Epics, and the Package and Container Registries.\n\n\nHigh-level migration phases:\n\n\n```mermaid\ngraph LR\n    subgraph Prerequisites\n        direction TB\n        A[\"Set up identity provider (IdP) and\u003Cbr/>provision users\"]\n        A --> B[\"Set up runners and\u003Cbr/>third-party integrations\"]\n        B --> I[\"Users enablement and\u003Cbr/>change management\"]\n    end\n    \n    subgraph MigrationPhase[\"Migration phase\"]\n        direction TB\n        C[\"Migrate source code\"]\n        C --> D[\"Preserve contributions and\u003Cbr/> format history\"]\n        D --> E[\"Migrate work items and\u003Cbr/>map to \u003Ca href=\"https://docs.gitlab.com/topics/plan_and_track/\">GitLab Plan \u003Cbr/>and track work\"]\n    end\n    \n    subgraph PostMigration[\"Post-migration steps\"]\n        direction TB\n        F[\"Create or translate \u003Cbr/>ADO pipelines to GitLab CI\"]\n        F --> G[\"Migrate other assets\u003Cbr/>packages and container images\"]\n        G --> H[\"Introduce \u003Ca href=\"https://docs.gitlab.com/user/application_security/secure_your_application/\">security\u003C/a> and\u003Cbr/>SDLC improvements\"]\n    end\n    \n    Prerequisites --> MigrationPhase\n    MigrationPhase --> PostMigration\n\n    style A fill:#FC6D26\n    style B fill:#FC6D26\n    style I fill:#FC6D26\n    style C fill:#8C929D\n    style D fill:#8C929D\n    style E fill:#8C929D\n    style F fill:#FFA500\n    style G fill:#FFA500\n    style H fill:#FFA500\n```\n\n\n## Planning your migration\n\n\n**To plan your migration, ask these questions:**\n\n\n- How soon do we need to complete the migration?\n\n- Do we understand what will be migrated?\n\n- Who will run the migration?\n\n- What organizational structure do we want in GitLab?\n\n- Are there any constraints, limitations, or pitfalls that need to be taken into account?\n\n\nDetermine your timeline, as it will largely dictate your migration approach. Identify champions or groups familiar with both ADO and GitLab platforms (such as early adopters) to help drive adoption and provide guidance.\n\n\n**Inventory what you need to migrate:**\n\n\n- The number of repositories, pull requests, and contributors\n\n- The number and complexity of work items and pipelines\n\n- Repository sizes and dependency relationships\n\n- Critical integrations and runner requirements (agent pools with specific capabilities)\n\n\nUse GitLab Professional Services's [Evaluate](https://gitlab.com/gitlab-org/professional-services-automation/tools/utilities/evaluate#beta-azure-devops) tool to produce a complete inventory of your entire Azure DevOps organization, including repositories, PR counts, contributor lists, number of pipelines, work items, CI/CD variables and more. If you're working with the GitLab Professional Services team, share this report with your engagement manager or technical architect to help plan the migration.\n\n\nMigration timing is primarily driven by pull request count, repository size, and amount of contributions (e.g. comments in PR, work items, etc). For example, 1,000 small repositories with few PRs and limited contributors can migrate much faster than a smaller set of repositories containing tens of thousands of PRs and thousands of contributors. Use your inventory data to estimate effort and plan test runs before proceeding with production migrations.\n\n\nCompare inventory against your desired timeline and decide whether to migrate all repositories at once or in batches. If teams cannot migrate simultaneously, batch and stagger migrations to align with team schedules. For example, in Professional Services engagements, we organize migrations into waves of 200-300 projects to manage complexity and respect API rate limits, both in [GitLab](https://docs.gitlab.com/security/rate_limits/) and [ADO](https://learn.microsoft.com/en-us/azure/devops/integrate/concepts/rate-limits?view=azure-devops).\n\n\nGitLab's built-in [repository importer](https://docs.gitlab.com/user/project/import/repo_by_url/) migrates Git repositories (commits, branches, and tags) one-by-one. Congregate is designed to preserve pull requests (known in GitLab as merge requests), comments, and related metadata where possible; the simple built-in repository import focuses only on the Git data (history, branches, and tags).\n\n\n**Items that typically require separate migration or manual recreation:**\n\n\n- Azure Pipelines - create equivalent GitLab CI/CD pipelines (consult with [CI/CD YAML](https://docs.gitlab.com/ci/yaml/) and/or with [CI/CD components](https://docs.gitlab.com/ci/components/)). Alternatively, consider using AI-based pipeline conversion available in Congregate.\n\n- Work items and boards - map to GitLab Issues, Epics, and Issue Boards.\n\n- Artifacts, container images (ACR) - migrate to GitLab Package Registry or Container Registry.\n\n- Service hooks and external integrations - recreate in GitLab.\n\n- [Permissions models](https://docs.gitlab.com/user/permissions/) differ between ADO and GitLab; review and plan permissions mapping rather than assuming exact preservation.\n\n\nReview what each tool (Congregate vs. built-in import) will migrate and choose the one that fits your needs. Make a list of any data or integrations that must be migrated or recreated manually.\n\n\n**Who will run the migration?**\n\n\nMigrations are typically run by a GitLab group owner or instance administrator, or by a designated migrator who has been granted the necessary permissions on the destination group/project. Congregate and the GitLab import APIs require valid authentication tokens for both Azure DevOps and GitLab.\n\n\n- Decide whether a group owner/admin will perform the migrations or whether you will grant a specific team/person delegated access.\n\n- Ensure the migrator has correctly configured personal access tokens (Azure DevOps and GitLab) with the scopes required by your chosen migration tool (for example, api/read_repository scopes and any tool-specific requirements). \n\n- Test tokens and permissions with a small pilot migration.\n\n**Note:** Congregate leverages file-based import functionality for ADO migrations and requires instance administrator permissions to run ([see our documentation](https://docs.gitlab.com/user/project/settings/import_export/#migrate-projects-by-uploading-an-export-file)). If you are migrating to GitLab.com, consider engaging Professional Services. For more information, see the [Professional Services Full Catalog](https://about.gitlab.com/professional-services/catalog/). Non-admin account cannot preserve contribution attribution!\n\n\n**What organizational structure do we want in GitLab?**\n\nWhile it's possible to map ADO structure directly to GitLab structure, it's recommended to rationalize and simplify the structure during migration. Consider how teams will work in GitLab and design the structure to facilitate collaboration and access management. Here is a way to think about mapping ADO structure to GitLab structure:\n\n\n```mermaid\ngraph TD\n    subgraph GitLab\n        direction TB\n        A[\"Top-level Group\"]\n        B[\"Subgroup (optional)\"]\n        C[\"Projects\"]\n        A --> B\n        A --> C\n        B --> C\n    end\n\n    subgraph AzureDevOps[\"Azure DevOps\"]\n        direction TB\n        F[\"Organizations\"]\n        G[\"Projects\"]\n        H[\"Repositories\"]\n        F --> G\n        G --> H\n    end\n\n    style A fill:#FC6D26\n    style B fill:#FC6D26\n    style C fill:#FC6D26\n    style F fill:#8C929D\n    style G fill:#8C929D\n    style H fill:#8C929D\n```\n\nRecommended approach:\n\n\n- Map each ADO organization to a GitLab group (or a small set of groups), not to many small groups. Avoid creating a GitLab group for every ADO team project. Use migration as an opportunity to rationalize your GitLab structure.\n\n- Use subgroups and project-level permissions to group related repositories.\n\n- Manage access to sets of projects by using GitLab groups and group membership (groups and subgroups) rather than one group per team project.\n\n- Review GitLab [permissions](https://docs.gitlab.com/ee/user/permissions.html) and consider [SAML Group Links](https://docs.gitlab.com/user/group/saml_sso/group_sync/) to implement an enterprise RBAC model for your GitLab instance (or a GitLab.com namespace).\n\n\n**ADO Boards and work items: State of migration**\n\n\nIt's important to understand how work items migrate from ADO into GitLab Plan (issues, epics, and boards).\n\n\n- ADO Boards and work items map to GitLab Issues, Epics, and Issue Boards. Plan how your workflows and board configurations will translate.\n\n- ADO Epics and Features become GitLab Epics.\n\n- Other work item types (e.g., user stories, tasks, bugs) become project-scoped issues.\n\n- Most standard fields are preserved; selected custom fields can be migrated when supported.\n\n- Parent-child relationships are retained so Epics reference all related issues.\n\n- Links to pull requests are converted to merge request links to maintain development traceability.\n\n\nExample: Migration of an individual work item to a GitLab Issue, including field accuracy and relationships:\n\n\n![Example: Migration of an individual work item to a GitLab Issue](https://res.cloudinary.com/about-gitlab-com/image/upload/v1764769188/ztesjnxxfbwmfmtckyga.png)\n\n\nBatching guidance:\n\n\n- If you need to run migrations in batches, use your new group/subgroup structure to define batches (for example, by ADO organization or by product area).\n\n- Use inventory reports to drive batch selection and test each batch with a pilot migration before scaling.\n\n\n**Pipelines migration**\n\n\nCongregate [recently introduced](https://gitlab.com/gitlab-org/professional-services-automation/tools/migration/congregate/-/merge_requests/1298) AI-powered conversion for multi-stage YAML pipelines from Azure DevOps to GitLab CI/CD. This automated conversion works best for simple, single-file pipelines and is designed to provide a working starting point rather than a production-ready `.gitlab-ci.yml` file. The tool generates a functionally equivalent GitLab pipeline that you can then refine and optimize for your specific needs.\n\n\n- Converts Azure Pipelines YAML to `.gitlab-ci.yml` format automatically.\n\n- Best suited for straightforward, single-file pipeline configurations.\n\n- Provides a boilerplate to accelerate migration, not a final production artifact.\n\n- Requires review and adjustment for complex scenarios, custom tasks, or enterprise requirements.\n\n- Does not support Azure DevOps classic release pipelines — [convert these to multi-stage YAML](https://learn.microsoft.com/en-us/azure/devops/pipelines/release/from-classic-pipelines?view=azure-devops) first.\n\n\nRepository owners should review the [GitLab CI/CD documentation](https://docs.gitlab.com/ci/) to further optimize and enhance their pipelines after the initial conversion.\n\n\nExample of converted pipelines:\n\n\n```yml \n\n# azure-pipelines.yml\n\ntrigger:\n  - main\n\nvariables:\n  imageName: myapp\n\nstages:\n  - stage: Build\n    jobs:\n      - job: Build\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          - task: Docker@2\n            displayName: Build Docker image\n            inputs:\n              command: build\n              repository: $(imageName)\n              Dockerfile: '**/Dockerfile'\n              tags: |\n                $(Build.BuildId)\n\n  - stage: Test\n    jobs:\n      - job: Test\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          # Example: run tests inside the container\n          - script: |\n              docker run --rm $(imageName):$(Build.BuildId) npm test\n            displayName: Run tests\n\n  - stage: Push\n    jobs:\n      - job: Push\n        pool:\n          vmImage: 'ubuntu-latest'\n        steps:\n          - checkout: self\n\n          - task: Docker@2\n            displayName: Login to ACR\n            inputs:\n              command: login\n              containerRegistry: '\u003Cyour-acr-service-connection>'\n\n          - task: Docker@2\n            displayName: Push image to ACR\n            inputs:\n              command: push\n              repository: $(imageName)\n              tags: |\n                $(Build.BuildId)\n\n```\n\n```yaml\n\n# .gitlab-ci.yml\n\nvariables:\n  imageName: myapp\n\nstages:\n  - build\n  - test\n  - push\n\nbuild:\n  stage: build\n  image: docker:latest\n  services:\n    - docker:dind\n  script:\n    - docker build -t $imageName:$CI_PIPELINE_ID -f $(find . -name Dockerfile) .\n  only:\n    - main\n\ntest:\n  stage: test\n  image: docker:latest\n  services:\n    - docker:dind\n  script:\n    - docker run --rm $imageName:$CI_PIPELINE_ID npm test\n  only:\n    - main\n\npush:\n  stage: push\n  image: docker:latest\n  services:\n    - docker:dind\n  before_script:\n    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY\n  script:\n    - docker tag $imageName:$CI_PIPELINE_ID $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n    - docker push $CI_REGISTRY/$CI_PROJECT_PATH/$imageName:$CI_PIPELINE_ID\n  only:\n    - main\n\n```\n\n**Final checklist:**\n\n\n- Decide timeline and batch strategy.\n\n- Produce a full inventory of repositories, PRs, and contributors.\n\n- Choose Congregate or the built-in import based on scope (PRs and metadata vs. Git data only).\n\n- Decide who will run migrations and ensure tokens/permissions are configured.\n\n- Identify assets that must be migrated separately (pipelines, work items, artifacts, and hooks) and plan those efforts.\n\n- Run pilot migrations, validate results, then scale according to your plan.\n\n\n## Running your migrations\n\n\nAfter planning, execute migrations in stages, starting with trial runs. Trial migrations help surface org-specific issues early and let you measure duration, validate outcomes, and fine-tune your approach before production.\n\n\nWhat trial migrations validate:\n\n\n- Whether a given repository and related assets migrate successfully (history, branches, tags; plus MRs/comments if using Congregate)\n\n- Whether the destination is usable immediately (permissions, runners, CI/CD variables, integrations)\n\n- How long each batch takes, to set schedules and stakeholder expectations\n\n\nDowntime guidance:\n\n\n- GitLab's built-in Git import and Congregate do not inherently require downtime.\n\n- For production waves, freeze changes in ADO (branch protections or read-only) to avoid missed commits, PR updates, or work items created mid-migration.\n\n- Trial runs do not require freezes and can be run anytime.\n\n\nBatching guidance:\n\n\n- Run trial batches back-to-back to shorten elapsed time; let teams validate results asynchronously.\n\n- Use your planned group/subgroup structure to define batches and respect API rate limits.\n\n\nRecommended steps:\n\n\n1. Create a test destination in GitLab for trials:\n\n\n  - GitLab.com: create a dedicated group/namespace (for example, my-org-sandbox)\n\n  - Self-managed: create a top-level group or a separate test instance if needed\n\n\n2. Prepare authentication:\n\n\n  - Azure DevOps PAT with required scopes.\n\n  - GitLab Personal Access Token with api and read_repository (plus admin access for file-based imports used by Congregate).\n\n\n3. Run trial migrations:\n\n\n  - Repos only: use GitLab's built-in import (Repo by URL)\n\n  - Repos + PRs/MRs and additional assets: use Congregate\n\n\n4. Post-trial follow-up:\n\n\n  - Verify repo history, branches, tags; merge requests (if migrated), issues/epics (if migrated), labels, and relationships.\n\n  - Check permissions/roles, protected branches, required approvals, runners/tags, variables/secrets, integrations/webhooks.\n\n  - Validate pipelines (`.gitlab-ci.yml`) or converted pipelines where applicable.\n\n\n5. Ask users to validate functionality and data fidelity.\n\n6. Resolve issues uncovered during trials and update your runbooks.\n\n7. Network and security:\n\n\n  - If your destination uses IP allow lists, add the IPs of your migration host and any required runners/integrations so imports can succeed.\n\n\n8. Run production migrations in waves:\n\n\n  - Enforce change freezes in ADO during each wave.\n\n  - Monitor progress and logs; retry or adjust batch sizes if you hit rate limits.\n\n\n9. Optional: remove the sandbox group or archive it after you finish.\n\n\n\u003Cfigure class=\"video_container\">\n  \u003Ciframe src=\"https://www.youtube.com/embed/ibIXGfrVbi4?si=ZxOVnXjCF-h4Ne0N\" frameborder=\"0\" allowfullscreen=\"true\">\u003C/iframe>\n\u003C/figure>\n\n\n## Terminology reference for GitLab and Azure DevOps\n\n| GitLab                                                           | Azure DevOps                                 | Similarities & Key Differences                                                                                                                                          |\n| ---------------------------------------------------------------- | -------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Group                                                            | Organization                                 | Top-level namespace, membership, policies. ADO org contains Projects; GitLab Group contains Subgroups and Projects.                                                   |\n| Group or Subgroup                                                | Project                                      | Logical container, permissions boundary. ADO Project holds many repos; GitLab Groups/Subgroups organize many Projects.                                                |\n| Project (includes a Git repo)                                    | Repository (inside a Project)                | Git history, branches, tags. In GitLab, a \"Project\" is the repo plus issues, CI/CD, wiki, etc. One repo per Project.                                                  |\n| Merge Request (MR)                                               | Pull Request (PR)                            | Code review, discussions, approvals. MR rules include approvals, required pipelines, code owners.                                                                     |\n| Protected Branches, MR Approval Rules, Status Checks             | Branch Policies                              | Enforce reviews and checks. GitLab combines protections + approval rules + required status checks.                                                                    |\n| GitLab CI/CD                                                     | Azure Pipelines                              | YAML pipelines, stages/jobs, logs. ADO also has classic UI pipelines; GitLab centers on .gitlab-ci.yml.                                                               |\n| .gitlab-ci.yml                                                   | azure-pipelines.yml                          | Defines stages/jobs/triggers. Syntax/features differ; map jobs, variables, artifacts, and triggers.                                                                   |\n| Runners (shared/specific)                                        | Agents / Agent Pools                         | Execute jobs on machines/containers. Target via demands (ADO) vs tags (GitLab). Registration/scoping differs.                                                         |\n| CI/CD Variables (project/group/instance), Protected/Masked       | Pipeline Variables, Variable Groups, Library | Pass config/secrets to jobs. GitLab supports group inheritance and masking/protection flags.                                                                          |\n| Integrations, CI/CD Variables, Deploy Keys                       | Service Connections                          | External auth to services/clouds. Map to integrations or variables; cloud-specific helpers available.                                                                 |\n| Environments & Deployments (protected envs)                      | Environments (with approvals)                | Track deploy targets/history. Approvals via protected envs and manual jobs in GitLab.                                                                                 |\n| Releases (tag + notes)                                           | Releases (classic or pipelines)              | Versioned notes/artifacts. GitLab Release ties to tags; deployments tracked separately.                                                                               |\n| Job Artifacts                                                    | Pipeline Artifacts                           | Persist job outputs. Retention/expiry configured per job or project.                                                                                                  |\n| Package Registry (NuGet/npm/Maven/PyPI/Composer, etc.)           | Azure Artifacts (NuGet/npm/Maven, etc.)      | Package hosting. Auth/namespace differ; migrate per package type.                                                                                                     |\n| GitLab Container Registry                                        | Azure Container Registry (ACR) or others     | OCI images. GitLab provides per-project/group registries.                                                                                                             |\n| Issue Boards                                                     | Boards                                       | Visualize work by columns. GitLab boards are label-driven; multiple boards per project/group.                                                                         |\n| Issues (types/labels), Epics                                     | Work Items (User Story/Bug/Task)             | Track units of work. Map ADO types/fields to labels/custom fields; epics at group level.                                                                              |\n| Epics, Parent/Child Issues                                       | Epics/Features                               | Hierarchy of work. Schema differs; use epics + issue relationships.                                                                                                   |\n| Milestones and Iterations                                        | Iteration Paths                              | Time-boxing. GitLab Iterations (group feature) or Milestones per project/group.                                                                                       |\n| Labels (scoped labels)                                           | Area Paths                                   | Categorization/ownership. Replace hierarchical areas with scoped labels.                                                                                              |\n| Project/Group Wiki                                               | Project Wiki                                 | Markdown wiki. Backed by repos in both; layout/auth differ slightly.                                                                                                  |\n| Test reports via CI, Requirements/Test Management, integrations  | Test Plans/Cases/Runs                        | QA evidence/traceability. No 1:1 with ADO Test Plans; often use CI reports + issues/requirements.                                                                     |\n| Roles (Owner/Maintainer/Developer/Reporter/Guest) + custom roles | Access levels + granular permissions         | Control read/write/admin. Models differ; leverage group inheritance and protected resources.                                                                          |\n| Webhooks                                                         | Service Hooks                                | Event-driven integrations. Event names/payloads differ; reconfigure endpoints.                                                                                        |\n| Advanced Search                                                  | Code Search                                  | Full-text repo search. Self-managed GitLab may need Elasticsearch/OpenSearch for advanced features.                                                                   |\n","2025-12-03","2026-01-16","https://res.cloudinary.com/about-gitlab-com/image/upload/v1749658924/Blog/Hero%20Images/securitylifecycle-light.png",[737,738],"Evgeny Rudinsky","Michael Leopard","Guide: Migrate from Azure DevOps to GitLab","Learn how to carry out the full migration from Azure DevOps to GitLab using GitLab Professional Services migration tools — from planning and execution to post-migration follow-up tasks.",{"featured":26,"template":13,"slug":742},"migration-from-azure-devops-to-gitlab",{"promotions":744},[745,759,770],{"id":746,"categories":747,"header":749,"text":750,"button":751,"image":756},"ai-modernization",[748],"ai-ml","Is AI achieving its promise at scale?","Quiz will take 5 minutes or less",{"text":752,"config":753},"Get your AI maturity score",{"href":754,"dataGaName":755,"dataGaLocation":239},"/assessments/ai-modernization-assessment/","modernization assessment",{"config":757},{"src":758},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/qix0m7kwnd8x2fh1zq49.png",{"id":760,"categories":761,"header":762,"text":750,"button":763,"image":767},"devops-modernization",[723,555],"Are you just managing tools or shipping innovation?",{"text":764,"config":765},"Get your DevOps maturity score",{"href":766,"dataGaName":755,"dataGaLocation":239},"/assessments/devops-modernization-assessment/",{"config":768},{"src":769},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138785/eg818fmakweyuznttgid.png",{"id":771,"categories":772,"header":774,"text":750,"button":775,"image":779},"security-modernization",[773],"security","Are you trading speed for security?",{"text":776,"config":777},"Get your security maturity score",{"href":778,"dataGaName":755,"dataGaLocation":239},"/assessments/security-modernization-assessment/",{"config":780},{"src":781},"https://res.cloudinary.com/about-gitlab-com/image/upload/v1772138786/p4pbqd9nnjejg5ds6mdk.png",{"header":783,"blurb":784,"button":785,"secondaryButton":790},"Start building faster today","See what your team can do with the intelligent orchestration platform for DevSecOps.\n",{"text":786,"config":787},"Get your free trial",{"href":788,"dataGaName":46,"dataGaLocation":789},"https://gitlab.com/-/trial_registrations/new?glm_content=default-saas-trial&glm_source=about.gitlab.com/","feature",{"text":491,"config":791},{"href":50,"dataGaName":51,"dataGaLocation":789},1772652103270]